Polyetheretherketone (or PEEK) is a thermoplastic polymer known for its high plasticity and toughness and has been widely employed as a material for a variety of load-bearing medical devices ranging from trauma implants to interspinal spacers and femoral stems. While being inherently chemically inert and therefore biocompatible and having very short lived post-radiation free radicals, PEEK presents different mechanical properties depending on its degree of crystallinity. It can be processed via extrusion, injection or compression moulding. However, these techniques do not allow high precision control over the fine morphological structure that strongly influences mechanical properties. Microinjection moulding, in contrast, makes it possible to produce fine details of medical implants with high precision and accuracy. Another advantage of this method is the controlled production of the material with heterogeneous structure due to variations in crystallinity. Having stiffness in the middle of the sample different from that at the edges enables a structure that mimics the bone/cartilage parts of an implant. This paper reports on the manufacturing of PEEK components by microinjection moulding, and their characterisation by physico-chemical (XRD, SAXS, TEM, FTIR, POM) and mechanical (tensile testing) means, in order to assess the suitability of use for biomedical application, such as spinal implants. We discuss the influence of such parameters as mould temperatures, injection speeds and hold pressures on the crystallinity and mechanical properties of the material.

In the pharmaceutical industry, enhanced process understanding resulting in superior control of product attributes, has the potential to save up to 20% of process engineering and product development costs during drug development. With the aim of achieving enhanced process understating, a novel approach for granulation of fine powders is presented. First, a mould with the desired particle shape and size is created using 3D printing followed by casting using elastomeric material. The formulation is prepared through wet massing and tested as a thin film on flat elastomeric membranes. The thin film itself can be a product but it also gives a good indication of coating performance before coating the patterned elastic membrane with the formulation i.e., 3D printed elastic mould granulation. Results show that following granulation and drying, granules of controlled size and shape (e.g. cubic and 500 μm), strength, friability and flowability can be formed. The method presented may allow for more robust process development in particle engineering.

Vegetation remains to be an important factor that can hinder the river flow. It needs innovative management scheme, in order
to adapt these changes and ensure sustainability of their multiple usages. Vegetation plays an important role in floods and
droughts adaptation within river system to alleviate any flood that may propagates from river to its surrounding. Vegetation within
river can also retard its flow to cause building-up of deposition, and further adding to uncertainty of water use under extreme
droughts. Due to these, it is important to study and understand vegetation drag behaviour toward flow in order to prevent flood
risk and water security with hydrological drought in the basin and any other negative impact caused by it. In this study, an
analytical approach for river flooding has been studied by improved representation of drag coefficient CD in flow velocity
distribution modelling. The analysis of flow parameters, i.e. Reynolds number, on the drag coefficient CD has been conducted.
The presented model has been used and analysed in open channel flows with flexible vegetation. In modelling, the flexible
vegetated channel layers were divided into vegetation, top of vegetation and water layer zones in the model. The balance of
forces for each layer has been established by validation using different reported measured data. The modelling results showed
reasonably corresponding prediction of velocity profile in flows with flexible vegetation.

This paper presented a new circular polarization reconfigurable antenna for 5G wireless
communications. The antenna, containing a semicircular slot, was compact in size and had a good
axial ratio and frequency response. Two PIN diode switches controlled the reconfiguration for both
the right-hand and left-hand circular polarization. Reconfigurable orthogonal polarizations were
achieved by changing the states of the two PIN diode switches, and the reflection coefficient |S11|
was maintained, which is a strong benefit of this design. The proposed polarization-reconfigurable
antenna was modeled using the Computer Simulation Technology (CST) software. It had a 3.4 GHz
resonance frequency in both states of reconfiguration, with a good axial ratio below 1.8 dB, and good
gain of 4.8 dBic for both modes of operation. The proposed microstrip antenna was fabricated on an
FR-4 substrate with a loss tangent of 0.02, and relative dielectric constant of 4.3. The radiating layer
had a maximum size of 18.3 18.3 mm2, with 50 W coaxial probe feeding.

In this paper, a compact microstrip band-pass filter (BPF) covering the 3.4 to 3.8 GHz spectrum bandwidth for 5G wireless communications is presented. The planar filter uses three resonators, each terminated by a via to hole ground at one end and a capacitor at the other end with 50 Ω transmission line impedances for input and output terminals. The coupling between the lines is adjusted to resonate at the centre frequency with third-order band-pass Butterworth properties. The proposed combline filter is designed on an alumina substrate with a relative dielectric constant of 9.8 and a very small size of 9×5×1.2 mm3. The proposed filter is simulated and

This study proposes a compact design of frequency-reconfigurable
antenna array for fifth generation (5G) cellular networks. Eight compact discrete-
fed slot antennas are placed on the top portion of a mobile phone printedcircuit-
board (PCB) to form a beam-steerable array. The frequency response of
the antenna can be reconfigured to operate at either 28 GHz or 38 GHz, two of
the candidate frequency bands for millimeter-wave (MM-Wave) 5G communications.
The reconfigurability function of the proposed design can be achieved
by implementing and biasing a pair of diodes across each T-shaped slot antenna
element. Rogers RT 5880 with thickness of 0.508 mm and properties of ε = 2.2
and δ = 0.0009 has been used as the antenna substrate. The antenna element is
very compact in size with a good end-fire radiation pattern in the frequency
bands of interest. The proposed beam-steerable array provides very good 3D
coverage. The simulation results show that the proposed design provides some
good characteristics fitting the need of the 5G cellular communications.

This paper presents a circular polarization reconfigurable antenna for 5G applications, which is compact in size and has good axial ratio and frequency response. The proposed microstrip antenna is designed on a FR-4 substrate with a relative dielectric constant of 4.3 and has a maximum size of 30×30 mm2 with 50 Ω coaxial probe feeding. This design has two PIN diode switches controlling reconfiguration between right hand circular polarization (RHCP) and left hand circular polarization (LHCP). To achieve reconfigurability, a C-slot rectangular patch antenna with truncated corner techniques is employed by cutting off two corners on the radiating patch. The proposed antenna has been simulated using CST microwave studio software: it has 3.35-3.77 GHz and 3.4-3.72 GHz bands for both states of reconfiguration, and each is suitable for 5G applications with a good axial ratio of less than 1.8 dB and good gain of 4.8 dB for both modes of operation.

Beamforming in multi-user MIMO (MU-MIMO) systems is
a vital part of modern wireless communication systems. Researchers
looking for best operational performance normally optimize the problem
and then solve for best weight solutions. The weight optimization
problem contains variables in numerator and dominator: this leads to
so-called variable coupling, making the problem hard to solve. Formulating
the optimization in terms of the signal to leakage and noise ratio
(SLNR) helps in decoupling the problem variables. In this paper we
study the performance of the SLNR with variable numbers of users and
handset antennas. The results show that there is an optimum and the capacity
curve is a concave over these two parameters. The performances
of two further variations of this method are also considered.

A computational network heat transfer model was utilised to model the potential of heat energy recovery at multiple locations from a city scale combined sewer network. The uniqueness of this network model lies in its whole system validation and implementation for seasonal scenarios in a large sewer network. The network model was developed, on the basis of a previous single pipe heat transfer model, to make it suitable for application in large sewer networks and its performance was validated in this study by predicting the wastewater temperature variation in a sewer network. Since heat energy recovery in sewers may impact negatively on wastewater treatment processes, the viability of large scale heat recovery across a network was assessed by examining the distribution of the wastewater temperatures throughout the network and the wastewater temperature at the wastewater treatment plant inlet. The network heat transfer model was applied to a sewer network with around 3000 pipes and a population equivalent of 79500. Three scenarios; winter, spring and summer were modelled to reflect seasonal variations. The model was run on an hourly basis during dry weather. The modelling results indicated that potential heat energy recovery of around 116, 160 & 207 MWh/day may be obtained in January, March and May respectively, without causing wastewater temperature either in the network or at the inlet of the wastewater treatment plant to reach a level that was unacceptable to the water utility.

Because of the recent worldwide construction expansion, new roads and buildings may be constructed over already existing buried infrastructures e.g. buried utility pipes, leading to excessive loads threatening their stability and longevity. Limited research studies are available to assess the effect of geogrid reinforcing layers inclusion on mitigating the additional stresses on buried structures due to cyclic loadings. In this research, large-scale fully instrumented laboratory tests were conducted to investigate the behaviour of flexible High-Density Polyethylene pipes (HDPE), in unreinforced and geogrid-reinforced sand, subjected to incrementally increasing cyclic loading, e.g. due to different vehicles capacities or load increase with passing time. Results illustrated that deformation rate in pipe and footing, strain generation rate in pipe and reinforcing layers are rapidly increased in the initial loading cycles, in particular during the first 300 cycles, and then the rate of change decreases significantly, as more cycles are applied. In the unreinforced case, increasing the pipe burial depth significantly reduced the generated deformation and strain in the pipe; however, it has a situational effect on the footing settlement, where it increased after pipe burial depth to its diameter ratio (H/D) of 2.5. In reinforced cases, deformation and strain significantly reduced with the increase in pipe burial depth and number of reinforcing layers. Measurement of strain illustrated that strain generated in the lower reinforcing layer is always higher than that recorded in the upper one, regardless pipe burial depth and value of applied load.

This paper proposes a stable and accurate object registration pipeline for markerless augmented
reality applications. We present two novel algorithms for object recognition and
matching to improve the registration accuracy from model to scene transformation via point
cloud fusion. Whilst the first algorithm effectively deals with simple scenes with few object
occlusions, the second algorithm handles cluttered scenes with partial occlusions for robust
real-time object recognition and matching. The computational framework includes a locally
supported Gaussian weight function to enable repeatable detection of 3D descriptors. We
apply a bilateral filtering and outlier removal to preserve edges of point cloud and remove
some interference points in order to increase matching accuracy. Extensive experiments
have been carried to compare the proposed algorithms with four most used methods. Results
show improved performance of the algorithms in terms of computational speed, camera
tracking and object matching errors in semi-cluttered and partial-occluded scenes.

Tranquility has a number of facets. Given the role that tranquility plays in societies, it is increasingly seen as an environmental indicator. Earlier, some have identified tranquility as contributing to health and wellbeing of individuals and the society, making it to be rooted in the context of sound natural ecosystems as a desirable environmental characteristic.
Previous studies have identified tranquility places as having links to nature and natural features, wild landscapes, naturally behaving wildlife and natural sounds. The question of how tranquility can be evaluated and the perception of tranquility by visitors is a continuous recurrence. This study therefore selected seven green open spaces in Hong Kong in an attempt to answer these and other questions that are arising. Although results vary, it however provides a perspective on how people perceive tranquil spaces as part of their leisure and recreation indulgence, given rise to the concept of eco-leisure.

This paper provides a critical review and discussion of major challenges with automotive aftertreatment systems from the viewpoint of the reliability of complex systems. The aim of this review is to systematically explore research efforts towards the three key issues affecting the reliability of aftertreatment systems: physical problems, control problems and fault diagnostics issues. The review covers important developments in technologies for control of the system, various methods proposed to tackle NOx sensor cross-sensitivity as well as fault detection and diagnostics methods, utilized on SCR, LNT and DPF systems. This paper discusses future challenges and research direction towards assured dependability of complex cyber-physical systems.

Biometric of Intent (BoI) is a Computer Vision
(CV) automation, using Artificial Intelligence (AI) techniques,
which presents a new approach that extends the reach of the
classic biometric identification process. It provides an efficient
mechanism which deters the threats raised by unknown
individuals who have deceitful intentions and who aim to deploy
unlawful operations such as terrorist attacks. In this context, our
proposed BoI model is based on a framework constructed upon
an automated machine learning facial expression analysis system
which can assist law enforcement agencies who intend to deploy a
systematic preventive security approach that aims to reduce the
risk of potential unlawful attacks by rogue individuals through
the evaluation of their emotional state in relation to their
malicious intent.

Cyber-attacks have been an increasing threat on
people and organisations, which led to massive unpleasant
impact. Therefore, there were many solutions to handle
cyber-attacks, including Intrusion Detection Systems (IDS),
Intrusion Prevention Systems (IPS). These solutions will provide
a huge number of alarms that produce more are false positives.
Therefore, the IDS tool result should be operated by a human
intelligent be filtered effectively the huge amount of alerts to
identify true positive attacks and perform accordingly to the
incident response rule. This requires the IT employees to have
enough knowledge and competency on operating IDS, IPS and
incident handling. This paper aims to examine the awareness of
cyber security threat among all IT employees, focusing on three
domains: Knowledge, Monitoring and Prevention.

Peer-to-Peer (P2P) network is increasingly
becoming the most important means of trading content
throughout the last years due to the constant evolvement of the
cyber world. This popularity made the P2P network susceptible
to the spread of malware. The detection of the cause of malware
propagation is now critical to the survival of P2P networks. This
paper offers a review of the current relevant mathematical
propagation models that have been proposed to date to predict
the propagation behavior of a malware in a P2P network. We
analyzed the models proposed by researchers and experts in the
field by evaluating their limitations and a possible alternative
for improving the analysis of the expected behavior of a
malware spread.

Variable-displacement vane oil pumps are increasingly employed in automotive powertrains for their efficiency benefits through reduced losses. However, confirming long life reliability of a new commodity based on limited data available from product development tests and early field experience is a significant challenge, which is addressed by the work presented in this paper. The approach presented combines physical examination of pumps returned from tests, with analysis of damage factors for pump wear progression, and an analysis of functional parameters for the powertrain system focused on the cause effect linkages across the systems hierarchy. The metrology results from physical measurements of used parts provide useful insights for the wear progression and the expected service performance of the pump. The paper also expands towards a data driven approach based on ECU data analysis that could provide a pathway towards the development of online health monitoring and diagnostics of the oil pumps.

Natural draft cooling towers are subjected to dynamic air temperature and humidity ratio of air throughout the day. Their performances based on steady state model is restricted to single air temperature and humidity ratio of air values and thus are not accurate. In this work, a dynamic model for a natural draft cooling tower is developed. Air temperature and relative humidity data for Johannesburg were acquired to develop dynamic correlations for these two parameters and are embedded in the process model together with the dynamic model of the collection basin of the tower. A simple algorithm is proposed to solve the resulting boundary value problem. Finally, the common perception that seawater/river water should be used instead of freshwater as cooling medium is tested via optimisation where the operating costs of the process for two cooling mediums is minimised. The freshwater has been found to be cost effective cooling medium.

For composite cellular beams, additional deflections occur due to the loss of bending and shear stiffness at the opening positions and also due to slip in the shear connectors caused by partial shear connection. Design formulae are presented for the additional deflection of composite beams with circular openings or for cellular beams as a function of the proportionate depth of the openings. The simplified formulae are calibrated against finite element results for both cellular and solid web beams and also against measured deflections of a 15.3 m composite cellular beam test. This additional deflection is presented as a function of flexural and shear terms that are a function of the span:depth ratio. For modelling of cellular beams to determine deflections, the circular opening may be represented by an equivalent rectangular opening of length equal to 70% of the opening diameter.

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